Overview
- Presents recent research on all aspects of machine learning and data mining for health care
- Focuses on general algorithms that can handle multiple sources of complex data in medical research databases
- Includes various successful machine learning algorithms for health care as well as applications and descriptions of actual systems
Part of the book series: Intelligent Systems Reference Library (ISRL, volume 186)
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Table of contents (10 chapters)
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Deep Features and Their Fusion
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Augmentation
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Medical Applications and Reviews
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Ethical Considerations
Keywords
About this book
This book introduces readers to the current trends in using deep learners and deep learner descriptors for medical applications. It reviews the recent literature and presents a variety of medical image and sound applications to illustrate the five major ways deep learners can be utilized: 1) by training a deep learner from scratch (chapters provide tips for handling imbalances and other problems with the medical data); 2) by implementing transfer learning from a pre-trained deep learner and extracting deep features for different CNN layers that can be fed into simpler classifiers, such as the support vector machine; 3) by fine-tuning one or more pre-trained deep learners on an unrelated dataset so that they are able to identify novel medical datasets; 4) by fusing different deep learner architectures; and 5) by combining the above methods to generate a variety of more elaborate ensembles. This book is a value resource for anyone involved in engineering deep learners for medical applications as well as to those interested in learning more about the current techniques in this exciting field. A number of chapters provide source code that can be used to investigate topics further or to kick-start new projects.
Editors and Affiliations
Bibliographic Information
Book Title: Deep Learners and Deep Learner Descriptors for Medical Applications
Editors: Loris Nanni, Sheryl Brahnam, Rick Brattin, Stefano Ghidoni, Lakhmi C. Jain
Series Title: Intelligent Systems Reference Library
DOI: https://doi.org/10.1007/978-3-030-42750-4
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: Springer Nature Switzerland AG 2020
Hardcover ISBN: 978-3-030-42748-1Published: 16 May 2020
eBook ISBN: 978-3-030-42750-4Published: 15 May 2020
Series ISSN: 1868-4394
Series E-ISSN: 1868-4408
Edition Number: 1
Number of Pages: XI, 284
Number of Illustrations: 59 b/w illustrations, 51 illustrations in colour
Topics: Computational Intelligence, Artificial Intelligence, Health Informatics, Biomedical Engineering and Bioengineering